The way to build software has changed due to escalated market trends and consumer needs. However, conventional methods of developing software cannot meet the new demands in the software industry. So, with the increased demand for speed to deliver products in the market, there is a need to have the technical capability to reach the market with a competitive product confirming its quality to the highest. This need has compelled the evolution of Continuous Integration (CI) and Continuous Delivery (CD).
Undoubtedly, Agile's emergence has accelerated the software development process to reach the market faster by splitting the software's functionality into modules, and developing the modules as per client priority and delivering the software in short sprints much sooner than waterfall methodology.
Faster time to market is the ultimate business goal of every organization and Agile has acted as an initiator to drive the journey of reaching faster time to market. Still, there was a long way for Agile adopters to travel to reach their destination. Continuous delivery has become the new vehicle for them to reach their destination sooner by streamlining and automating the process of build-deploy-deliver.
Continuous Integration is the process of automating build deployment, leveraging a CI tool like Jenkins, Bamboo, Octopus Deploy, Travis CI, and others. When developers commit code with bug fixes or implementation of a new feature, CI opens the door to CD to achieve more frequent software releases, reaching customers sooner with improved software. However, there is a gap created between the two endpoints CI and CD because of sluggish software testing practices, which needs to be bridged to deliver quality software faster.
The sluggish testing practices, which are manual and tedious or didn’t align test automation with CI/CD processes, have to be refined to be continuous. Therefore, there is a need for continuous testing capabilities, achieved by blending the process of triggering automated regression test suites’ execution from the CI server with automated build deployment. This way, whenever a new build with bug fixes or new features arrives, regression test suites will be executed, leading to continuous testing, and based on the bugs reported, a decision can be made whether to release or not. The ultimate business goal – achieving faster time to market, the destination every organization strives to reach – can be reached.
The release time for software can be further reduced with the capability to automate build deployment into production, which means having an automated process of decision-making to release or not release based on the severity of the bugs reported after continuous testing.